Ecological Indicators 21 (2012) 17–29
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Ecological Indicators
journal homepage: www.elsevier.com/locate/ecolind
Mapping ecosystem service supply, demand and budgets
Benjamin Burkharda,∗ , Franziska Krolla , Stoyan Nedkovb , Felix Müllera
a
b
Institute for the Conservation of Natural Resources, Department of Ecosystem Management, Ecology Centre, Christian Albrechts University Kiel, Olshausenstr. 40, 24098 Kiel, Germany
Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of Sciences, Acad. G. Bonchev Street, bl. 3, 1113 Sofia, Bulgaria
a r t i c l e
i n f o
Keywords:
Ecosystem functions
Ecological integrity
Ecosystem service footprint
CORINE land cover
Ecosystem service maps
GIS
a b s t r a c t
Among the main effects of human activities on the environment are land use and resulting land cover
changes. Such changes impact the capacity of ecosystems to provide goods and services to the human
society. This supply of multiple goods and services by nature should match the demands of the society, if
self-sustaining human–environmental systems and a sustainable utilization of natural capital are to be
achieved. To describe respective states and dynamics, appropriate indicators and data for their quantification, including quantitative and qualitative assessments, are needed. By linking land cover information
from, e.g. remote sensing, land survey and GIS with data from monitoring, statistics, modeling or interviews, ecosystem service supply and demand can be assessed and transferred to different spatial and
temporal scales. The results reveal patterns of human activities over time and space as well as the capacities of different ecosystems to provide ecosystem services under changing land use. Also the locations
of respective demands for these services can be determined. As maps are powerful tools, they hold high
potentials for visualization of complex phenomena. We present an easy-to-apply concept based on a
matrix linking spatially explicit biophysical landscape units to ecological integrity, ecosystem service
supply and demand. An exemplary application for energy supply and demand in a central German case
study region and respective maps for the years 1990 and 2007 are presented. Based on these data, the
concept for an appropriate quantification and related spatial visualization of ecosystem service supply
and demand is elaborated and discussed.
© 2011 Elsevier Ltd. All rights reserved.
1. Introduction
There is no doubt about the increasing popularity of the ecosystem service concept in contemporary science (Seppelt et al., 2011;
Fisher et al., 2009). The longer the conceptual orientation phase of
the ecosystem service approach has been lasting, the more obvious become the needs for practical applications of the concept
(Daily et al., 2009; Burkhard et al., 2010). These applications are
necessary in order to improve the concept and make it an acknowledged tool for natural resource management (Kienast et al., 2009).
The quantification and implementation of ecosystem goods and
services have been among the biggest challenges of current ecosystem science (Wallace, 2007). Monetary approaches like cost-benefit
analyses, contingent valuations or willingness-to-pay assessments
are useful attempts (Farber et al., 2002) but their outcomes are often
disappointing due to the economic focus and the lack of appropriate
pricing methods, e.g. for non-marketed goods and services (Ludwig,
2000; Spangenberg and Settele, 2010).
The provision of ecosystem services depends on biophysical
conditions and changes over space and time due to human induced
∗ Corresponding author. Tel.: +49 431 880 1230; fax: +49 431 880 4083.
E-mail address: [email protected] (B. Burkhard).
1470-160X/$ – see front matter © 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ecolind.2011.06.019
land cover, land use and climatic changes. Spatial patterns of land
cover and land cover change can be linked to large regions and
provide direct measures of human activity (Riitters et al., 2000).
Because of the spatial peculiarity of ecosystem services, mapping
their distributions and changes over time has the potential to aggregate complex information. This visualization of ecosystem services
can be used by decision makers, e.g. land managers, as a powerful tool for the support of landscape sustainability assessments
(Swetnam et al., 2010). Unfortunately, there is a clear lack of information relevant to local scale decision making (Turner and Daily,
2008). Therefore, the explicit quantification and mapping of ecosystem services are considered as one of the main requirements for
the implementation of the ecosystem services concept into environmental institutions and decision making (Daily and Matson,
2008).
In recent years, many new ecosystem service mapping
approaches have been developed and applied at different spatial scales by several authors. For a more detailed review of
recent approaches to ecosystem service mapping at different spatial scales we refer to Burkhard et al. (2009). Novel studies and
approaches on ecosystem service mapping are presented in this
special issue (e.g. Schneiders et al., 2012; Koschke et al., 2012;
Haines-Young et al., 2012; Nedkov and Burkhard, 2012; Scolozzi
et al., 2012).
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B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
However, the direct comparison of ecosystem service supply
and demand in spatially explicit maps is rather rare in spite of the
wide agreement about the importance of including the demand
side into ecosystem service assessments (van Jaarsveld et al., 2005;
McDonald, 2009). Paetzold et al. (2010) note that the status of an
ecosystem service is influenced not only by its provision, but also
by human needs and the desired level of provision for this service
by the society, which connects supply and demand of ecosystem
services inseparably (Syrbe and Walz, 2012). Paetzold et al. (2010)
developed a framework for the assessment of ecological quality
which considers the supply as well as the demand of ecosystem
services. van Jaarsveld et al. (2005) present a practical application
of ecosystem supply and demand mapping at the subcontinental scale for Africa, whereas (Kroll et al., 2012) provide a method
for the quantification and mapping of ecosystem services at the
regional scale for a rural-urban region in eastern Germany. These
maps can be used by decision makers for the identification of
supply–demand mismatches across landscapes and their changes
over time (Paetzold et al., 2010). However, caution and patience are
still needed as the expectations from practitioners are already very
high, but most of the maps might still need further refinement with
more detailed spatial data and better socio-economic information
(Kienast et al., 2009).
When assessing and mapping ecosystem service supply and
demand, the problem of a clear distinction between ecosystem
functions, services and benefits is of high relevance (de Groot et al.,
2010; Haines-Young and Potschin, 2010; Burkhard et al., 2010).
For several practical reasons, the commonly used definition from
the Millennium Ecosystem Assessment “ecosystem services are the
benefits humans obtain from nature” (MA, 2005) and the related
four categories of supporting, provisioning, regulating and cultural
services are not always appropriate (Seppelt et al., 2011, 2012;
Wallace, 2007). As Fisher and Turner (2008) point out, we have
to delineate between ends and means if we want to operationalize
ecosystem services. Therefore, Boyd and Banzhaf (2007) introduced
the term final ecosystem services which are components of nature
directly enjoyed, consumed or used to yield human well-being.
Most of the other components and functions of an ecosystem would
then be intermediate products respectively intermediate services.
This goes along with Fisher and Turner (2008) who propose that
ecosystem services’ benefits must have a direct relation to human
well-being. For example, nutrient cycling is an ecological function, not an ecosystem service (Boyd and Banzhaf, 2007). However,
the distinction between intermediate and final services is often
observer-based and depending on rather subjective decisions.
Therefore, we follow a framework which integrates the concept
of ecological integrity as the base for the supply of regulating, provisioning and cultural ecosystem services (Müller and Burkhard,
2007). Ecological integrity means the preservation against nonspecific ecological risks that are general disturbances of the
self-organizing capacity of ecological systems. This self-organizing
capacity is based on structures and processes in ecosystems, and
appropriate indicators for their description have been defined and
applied in several case studies (Müller, 2005; Burkhard and Müller,
2008). Land use and related land cover modifications have a strong
impact on ecological integrity. Alterations of ecological integrity
lead to increasing or decreasing supplies of selected or bundles of
ecosystem services, on which human societies depend.
If the supply of ecosystem services is changed, human societies’
demands for ecosystem services might not be fulfilled anymore.
However, it is difficult in today’s complex and globalized world to
follow the tracks and define the origin of goods and services consumed by people in a certain region. Many goods and services are
imported from more or less remote places. In this way, the environmental impacts of ecosystem service generation are exported
and leave a biodiversity and ecosystem service footprint elsewhere
(Burkhard and Kroll, 2010). Finding an acceptable and equitable
level of ecosystem service footprints and an appropriate balance
of local ecosystem service supply and demand are important steps
toward sustainability. So far, few approaches exist which deal with
the relations between local demands and ecosystem service provision elsewhere (Seppelt et al., 2011).
The following definitions are the conceptual background of our
approach:
• Supply of ecosystem services refers to the capacity of a particular area to provide a specific bundle of ecosystem goods
and services within a given time period. Here, capacity refers
to the generation of the actually used set of natural resources
and services. Thus, it is not similar to the potential supply
of ecosystem services in a certain ecosystem, which would
be the hypothetical maximum yield of selected optimized
services.
• Demand for ecosystem services is the sum of all ecosystem
goods and services currently consumed or used in a particular area over a given time period. Up to now, demands are
assessed not considering where ecosystem services actually
are provided. These detailed provision patterns are part of
the:
• Ecosystem service footprint which (closely related to the ecological footprint’s concept; Rees, 1992) calculates the area
needed to generate particular ecosystem goods and services
demanded by humans in a certain area in a certain time.
Different aspects of ecosystem service generation are considered (production capacities, waste absorption, etc.).
According to our definitions, the regional supply of ecosystem
goods and services is directly determined by the regional ecological integrity which is influenced by human actions and decisions
such as land cover change, land use and technical progress. Human
well-being (economic, social and personal well-being) is based
on benefits derived from the people’s actual use of ecosystem
goods and services. This actual use of ecosystem goods and services is the demand side of this supply and demand chain (EEA,
2010). The impacts on the demand side are manifold and can
include policies, population dynamics, economic factors, marketing, trends, advertising, cultural norms and governance (Curran
and de Sherbinin, 2004). Fig. 1 illustrates the conceptual framework which the ecosystem service supply–demand assessments
and mapping have been developed upon.
In this context, the following aims were defined for this paper:
- to present a clear and easy-to-apply concept to map ecosystem
service supply and demand as well as supply and demand budgets, to derive a concept that is applicable at different scales for
various case study regions and that allows for comparison of different ecosystem services, and
- to support the development of simple tools for landscape managers to support sustainability assessments.
2. Materials and methods
We propose a non-monetary evaluation scheme based on indicators which are categorized and mapped in relation to relative
supply/demand scales. The applied method of ecosystem service
supply mapping has been presented before in Burkhard et al.
(2009). The ecosystem service demand mapping and the final
ecosystem service budgeting are added as new components to
ecosystem service mapping approaches.
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
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Fig. 1. Conceptual framework linking ecosystem integrity, ecosystem services and human well-being as supply and demand sides in human–environmental systems.
2.1. Indicators for ecological integrity and ecosystem services
The derivation of suitable indicators for the assessment of
ecosystem functions and their capacities to supply services is an
important step in order to know what will be evaluated. Appropriate ecosystem service indicators need to be quantifiable, sensitive
to changes in land cover,1 temporarily and spatially explicit and
scalable (van Oudenhoven et al., 2012).
Ecosystem functionality can be described by ecological integrity
and respective indicators have been elaborated in detail in Müller
(2005). These indicators describe structures and processes relevant for the long-term functionality and self-organizing capacity
of ecosystems. Structures relate to numbers and characteristics of,
e.g. selected species (biotic diversity) and physical habitat components (abiotic heterogeneity). Processes refer to ecosystem energy
budgets (exergy capture; e.g. biomass production), matter budgets
(nutrient storage and loss) and water budgets (biotic water flows
and metabolic efficiency). Table 1 provides short rationales and
suggests potential indicators to describe and quantify ecological
integrity and ecosystem services.
In addition to ecological integrity, regulating ecosystem services relate to ecosystem functions also (see Table 1). As they are
difficult to quantify, most assessments are based on model calculations (Jørgensen and Nielsen, 2012). Moreover, some components
of regulating services are overlapping with ecological integrity
processes; for example processes related to nutrient or water regulation. Therefore, a high risk of merging and double-counting of
ecological integrity variables and regulating ecosystem services is
inherent. This has to be recognized when interpreting the results.
Production and trade numbers as well as products’ market prices
are appropriate indicators for provisioning ecosystem services.
Hence, provisioning services seem to be relatively easy to quantify
but, cornered or changing markets and supplies, resource scarcity
or altering production and trade patterns have to be considered.
Assessments of cultural ecosystem services are rather subjective
and value-laden as each individual or each group of individuals has
different value systems and demands (MA, 2005). Several factors
like experience, habits, belief systems, behavioral traditions and
judgment as well as lifestyles have to be considered. All of them are
related more to the observer than to ecosystem conditions (Kumar
and Kumar, 2008; Hansen-Möller, 2009). Nevertheless, there has
been a lot of scientific progress with regard to the understanding of
landscapes’ role for, e.g. cultural identity (Hunziker et al., 2007; Fry
et al., 2009). There are also issues of clear conceptual delineation of
cultural ecosystem service categories and their proper localization
in space (Gee and Burkhard, 2010; Frank et al., 2012). The identification of spatially explicit units for cultural ecosystem services
to which functions, benefits and values can be assigned is perhaps
1
Land cover refers to features that cover the earth‘s surface whereas land use
documents how people are using the land (NOAA, 2009). Remote sensing data, for
example, provide a logical combination of land cover and land use as it can be tracked
from space. This latter combination of land cover and land use was used under the
term “land cover” in the following.
more challenging than for the other ecosystem service categories
(Haines-Young and Potschin, 2007).
Therefore, we suggest only two classes of cultural ecosystem
services here (recreation and aesthetic values and intrinsic value of
biodiversity; Table 1) and give space for defining further case study
specific cultural ecosystem services. Nevertheless, quantifications
based on interviews, questionnaires or additional information
sources can provide useful and spatially explicit results (Sherrouse
et al., 2010). For certain cultural ecosystem services, for example
recreation, tourist numbers or the numbers of overnight stays at
particular locations are applied. The intrinsic value of species and
biodiversity has been placed within the group of cultural ecosystem
services (Table 1). This may not be the most appropriate position
for the appreciation of nature and species diversity as such (besides
their contribution to human welfare), but in many of the available ecosystem service concepts biodiversity indicators were not
considered sufficiently or even not considered at all (TEEB, 2010).
Therefore, cultural ecosystem services may be the most suitable of
the currently defined ecosystem service categories to reflect the
idea of intrinsic values of species and nature.
2.2. Mapping landscape’s capacities to supply ecosystem services
Different ecosystems have different functions based on their
structures and processes (i.e. their integrity). Consequently, their
capacities to supply particular ecosystem services which are used
by humans can vary strongly (Bastian et al., 2012). The individual
ecosystem capacities to supply services are strongly linked to (a)
natural conditions; e.g. natural land cover (vegetation foremost),
hydrology, soil conditions, fauna, elevation, slope and climate as
well as (b) human impacts; mainly land use but also emissions,
pollution, etc. All this information and related data should be as
detailed as possible, in a relevant resolution and at an appropriate
scale when defining the capacities of different ecosystems to supply
services. Land cover information from remote sensing, land survey, simulation models, and statistical data are appropriate starting
points. By integrating these features with further data, the state of
ecosystems and their capacities to supply ecosystem services can
be assessed and transferred to maps of different spatial and temporal scales. The results reveal patterns of natural conditions and
human activities over time and the capacities of different ecosystems to supply ecosystem services considering current states and
real or potential changes in land use.
To start mapping ecosystem service capacities, we used
satellite-based CORINE land cover data from the European Union.
CORINE provides classified spatial land cover data in GIS format
ready for use. The hierarchically organized three-level CORINE
nomenclature (EEA, 1994) was used to define the different European land cover types in the sense of service providing ecosystems.
The CORINE system includes 44 land cover classes grouped into
(1) artificial surfaces, (2) agricultural areas, (3) forests and seminatural areas, (4) wetlands, and (5) water bodies. The GIS data
in the European CORINE data base contain a minimum mapping
unit (MMU) of 25 ha. Additional national datasets are available on
a 100 m grid, a 250 m grid and a 1 km grid for the years 1990, 2000
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B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
Table 1
List of ecological integrity and ecosystem service components with rationales and potential indicators.
Ecological integrity
Abiotic heterogeneity
Biodiversity
Biotic water flows
Metabolic efficiency
Exergy capture
Reduction of nutrient loss
Storage capacity
Regulating ecosystem services
Local climate regulation
Global climate regulation
Flood protection
Groundwater recharge
Air quality regulation
Erosion regulation
Nutrient regulation
Water purification
Pollination
Provisioning ecosystem services
Crops
Livestock
Fodder
Capture fisheries
Aquaculture
Wild foods
Timber
Wood fuel
Energy (biomass)
Biochemicals and medicine
Freshwater
Cultural ecosystem services (selection)
Recreation & aesthetic values
Intrinsic value of biodiversity
Rationales
Potential indicators
The provision of suitable habitats for different species, for
functional groups of species and for processes is essential
for the functioning of ecosystems.
The presence or absence of selected species, (functional)
groups of species, biotic habitat components or species
composition.
Referring to the water cycling affected by plant processes
in the system.
Referring to the amount of energy necessary to maintain a
specific biomass, also serving as a stress indicator for the
system.
The capability of ecosystems to enhance the input of
usable energy. Exergy is derived from thermodynamics
and measures the energy fraction that can be transformed
into mechanical work. In ecosystems, the captured exergy
is used to build up biomass (e.g. by primary production)
and structures.
Referring to the irreversible output of elements from the
system, the nutrient budget and matter flows.
Is referring to the nutrient, energy and water budgets of
the system and the capacity of the system to store them
when available and to release them when needed.
Abiotic habitat components’ diversity indices;
Heterogeneity indices, e.g. humus contents in the soil;
Number/area of habitats
Indicator species representative for a certain phenomenon
or sensitive to distinct changes
Changes in land cover can locally affect temperature, wind,
radiation and precipitation.
Ecosystems play an important role in climate by either
sequestering or emitting greenhouse gases.
Natural elements dampening extreme flood events
The timing and magnitude of runoff, flooding, and aquifer
recharge can be strongly influenced by changes in land
cover, including, in particular, alterations that change the
water storage potential of the system, such as the
conversion of wetlands or the replacement of forests with
croplands or croplands with urban areas.
The capacity of ecosystems to remove toxic and other
elements from the atmosphere.
Vegetative cover plays an important role in soil retention
and the prevention of landslides.
The capacity of ecosystems to carry out (re)cycling of, e.g.
N, P or others.
Ecosystems have the capacity to purify water but can also
be a source of impurities in fresh water.
Ecosystem changes affect the distribution, abundance, and
effectiveness of pollinators. Wind and bees are in charge of
the reproduction of a lot of culture plants.
Temperature, albedo, precipitation, wind; Temperature
amplitudes; Evapotranspiration
Source-sink of water vapour, methane, CO2
Transpiration/total evapotranspiration
Respiration/biomass (metabolic quotient)
Net primary production; Leaf area index LAI
Leaching of nutrients, e.g. N, P
Solved organic matter; N, Corg in the soil; N, C in biomass
Number of floods causing damages
Groundwater recharge rates
Leaf area index; Air quality amplitudes
Loss of soil particles by wind or water; vegetation cover
N, P or other nutrient turnover rates
Water quality and quantity
Amount of plant products; Distribution of plants;
Availability of pollinators
Cultivation of edible plants.
Keeping of edible animals.
Cultivation and harvest of animal fodder.
Catch of commercially interesting fish species, which are
accessible for fishermen.
Animals kept in terrestrial or marine aquaculture.
Harvest of, e.g. berries, mushrooms, wild animal hunting
or fishing.
Presence of trees or plants with potential use for timber.
Presence of trees or plants with potential use as fuel.
Presence of trees or plants with potential use as energy
source.
Production of biochemicals, medicines.
Presence of freshwater.
Plants/ha; kJ/ha
Animals/ha; kJ/ha
Fodder plants/ha; kJ/ha
Fishes available for catch/ha; kJ/ha
Refers specifically to landscape and visual qualities of the
resp. case study area (scenery, scenic beauty). The benefit
is the sense of beauty people get from looking at the
landscape and related recreational benefits.
The value of nature and species themselves, beyond
economic or human benefits.
Number of visitors or facilities; Questionnaires on personal
preferences
Based on de Groot et al. (2010), Burkhard et al. (2009), Müller and Burkhard (2007) and MA (2005).
+ further case study specific cultural ecosystem services and indictors.
Number of animals/ha; kJ/ha
Plant biomass/ha; Animals available/ha; kJ/ha
Wood/ha; kJ/ha
Wood or plant biomass/ha; kJ/ha
Wood or plant biomass/ha; kJ/ha
Amount or number of products; kg/ha
Liters or m3 /ha
Number of endangered, protected or rare species or
habitats
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
21
Table 2
List of established ecosystem service case studies used as information source for the derivation of the ecosystem service supply and demand assessment; including spatial
scales, relative data availability (+++ = excellent, ++ = good, + = sufficient) and References.
Study site
Spatial scale
Data availability
References
Finnish Lapland
Malki Iskar basin, Bulgaria
German North Sea
Schleswig-Holstein (Kielstau, Bornhöved, Ritzerau, Sylt), Germany
Leipzig-Halle, Germany
Himalaya, Nepal
Thailand
Three Gorges Dam, China
South East Asia (Vietnam, Malaysisa, Philippines)
Regional
Regional
Regional
Local – regional
Regional
Regional
Regional
Local – regional
Local – regional
++
++
+++
++
+++
++
+++
+
+
Vihervaara et al. (2010)
Nedkov and Burkhard, 2012
Lange et al. (2010); Gee and Burkhard (2010)
Schmidt (2008)
Kroll et al. (2012)
Tamang (2011)
Graterol (2011)
Still to be written
Still to be written
and 2006. Basic CORINE data can be downloaded for free from the
EEA website (http://dataservice.eea.europa.eu/). Data with higher
resolution can be purchased at marginal costs. For the mapping
approach presented in this paper, CORINE data sets in ArcGIS polygon format with 25 ha MMU were applied.
One main problem in almost all ecosystem service evaluations is
the identification of appropriate indicators and data to quantify the
broad range of ecosystem services (Seppelt et al., 2011; Wallace,
2007). One solution can be to make use of expert evaluations in
order to gain an overview and see trends for ecosystem service
assessments (Burkhard et al., 2009; Scolozzi et al., 2012; Busch et al.,
2012). The general assessment approach presented here is based
on values which were derived mainly by the authors as hypotheses linking different land cover types with ecosystem service supply
capacities and demands for ecosystem services. In subsequent analyses, the expert evaluation values can successively be replaced by
data from monitoring, measurements, computer-based modeling,
targeted interviews or statistics. This has been done successfully in
several case studies on regional scales; like the example presented
in Section 2.5, in Vihervaara et al. (2010), Nedkov and Burkhard
(2012) or Burkhard et al. (2009). Table 2 provides an overview on
the case studies where comparable ecosystem service assessments
have been carried out. Maes et al. (2011) applied a similar approach
on a continental scale, developing an ecosystem service atlas for
whole Europe.
We suggest a matrix linking 7 ecological integrity indicators
and 22 ecosystem services (on the x-axis) to 44 land cover types
(on the y-axis). The selection of the ecological integrity indicators
was based on Müller (2005); because these indicators represent
the main components of ecosystem functionality. Our selection of
ecosystem services is based on a combination of different ecosystem service lists provided in recent literature (de Groot et al., 2010;
TEEB, 2010; Müller and Burkhard, 2007; MA, 2005). The 44 land
cover classes originate from the CORINE nomenclature (EEA, 1994).
At the intersections (altogether 1276), the different land cover
types’ capacities to support ecological integrity or to provide particular services were assessed (first qualitatively; in the following case
study also quantitatively) on a scale consisting of: 0 = no relevant
capacity of the particular land cover type to support the selected
ecological integrity component or to supply the selected ecosystem
service, 1 = low relevant capacity, 2 = relevant capacity, 3 = medium
relevant capacity, 4 = high relevant capacity and 5 = very high relevant capacity (Fig. 2).
The matrix values are based on experience from different case
studies in different European regions (see list in Table 2) and have
to be considered as hypotheses of possible capacities of ecosystem
service provision (Burkhard et al., 2009). Naturally, there is a
high dependence on the observer’s experience, knowledge and
objectivity which service supplies are supposed to be relevant
and how to value them. However, this relative 0–5 scale offers
a way of evaluating alternatively to monetary accounting or
value-transfer methods. Nevertheless, the values will be checked
carefully in further case studies and substituted by numbers
from respective research, monitoring or statistics whenever
available.
Fig. 2 reveals rather high capacities of many near-natural land
cover types (forests, wetlands, water bodies, green urban areas,
certain agricultural areas) to support ecological integrity. High
capacities to provide several ecosystem services can be found
for the different forest land cover types, peatlands, moors and
heathlands. The highly human-modified land cover types (urban
fabric, industrial or commercial areas, mineral extraction and dump
sites) have very low or no relevant capacities to support ecological integrity or to provide regulating and provisioning ecosystem
services. A similar trend was found for cultural ecosystem services
which is consistent with several studies on human perception and
preferences of landscapes. For instance, Hartig and Staats (2006)
carried out experiments on human preferences of landscapes for
recreation (i.e. recovery, reflection and social stimulation). They
found a clear preference of natural landscapes (forests in their
study) compared to urban areas. Palmer (2004) applied landscape metrics (landscape composition and configuration) to predict
people’s perception of landscapes, thus adding behavioral and perceptual components into landscape pattern analyses. The results
showed a clear preference of “natural-appearing” landscapes with
complex patterns of edges.
By linking the 0–5 values to appropriate spatial data in GIS,
estimates of ecosystem service supply can be mapped in spatially
explicit units of similar biophysical settings (e.g. land cover types in
combination with soil types, hydrological and climatic conditions).
In the GIS, the ecosystem service supply matrix (Fig. 2) was joined
with the polygon attribute table using the CORINE land cover code
field as common identifier field. The following case study application will apply the procedure described above for an example of
energy provisioning ecosystem services.
2.3. Mapping human demands for ecosystem services
By definition, an ecosystem service is only a service, if there is
a (human) benefit. Without human beneficiaries, ecosystem functions and processes are not services (according to Fisher et al.,
2009). In other words, there must be a certain demand by people to
use a particular ecosystem service. To assess demands for ecosystem services, data on their actual use are needed. This information
can be derived from statistics, modeling, socio-economic monitoring or interviews. A matrix similar to the one for the ecosystem
service supply assessment was derived, showing initial hypotheses
on demands for ecosystem services (Fig. 3). The different (CORINE)
land cover types are again shown on the y-axis. On the x-axis, the
regulating, provisioning and cultural ecosystem services are listed.
Note that ecological integrity components are not included in the
demand matrix. Ecological integrity indicates ecosystem functions
which do not support human well-being directly (Fig. 1). The values in the demand matrix (Fig. 3) indicate: 0 = no relevant demand
from people within the particular land cover type for the selected
ecosystem service; 1 = low relevant demand; 2 = relevant demand;
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B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
Fig. 2. Assessment matrix illustrating the capacities of different land cover classes to support ecological integrity (column at the left side) and to supply ecosystem services
(the three columns at right). The values/colors indicate the following capacities:0/rosy = no relevant capacity; 1/grey green = low relevant capacity; 2/light green = relevant
capacity; 3/yellow green = medium relevant capacity; 4/blue green = high relevant capacity; and 5/dark green = very high relevant capacity (after Burkhard et al., 2009).
3 = medium relevant demand; 4 red = high relevant demand; and
5 = very high relevant demand.
The matrix of Fig. 3 clearly shows that demands for ecosystem services are highest in human-dominated land cover types
(in the upper part of the matrix). The highest demand values
can be found in the urban, industrial and commercial areas. The
more near-natural land cover types are characterized by generally
lower population numbers and less ecosystem service-consuming
activities and consequently, lower demand rates. The agricultural
land cover types show characteristic high demands for regulating ecosystem services (e.g. nutrient regulation, water purification,
pollination). Using similar spatially explicit units as during the
ecosystem service supply assessment, respective maps of ecosystem services demands can be produced.
−5 = demand exceeds supply significantly = strong undersupply;
via 0 = demand = supply = neutral balance; to 5 = supply exceeds the
demand significantly = strong oversupply. Empty fields indicate
that there is neither a relevant supply of nor a relevant demand for
the particular ecosystem service. For more detailed information on
actual supply–demand patterns including specific areas of supply
and demand, an ecosystem service footprint could be calculated.
The pattern emerging in Fig. 4 indicates that there is an obvious undersupply of ecosystem services in the human-dominated
land cover types, especially in the urban, industrial or commercial
areas. The more near-natural land cover types again, and especially
the forested areas, are characterized by many ecosystem services’
supplies exceeding their demands.
2.4. Mapping budgets of ecosystem services’ supply and demand
2.5. Exemplary quantification of energy supply and demand in
the rural-urban region Leipzig-Halle
For analyzing source and sink dynamics and to identify flows
of goods and services, the information in the matrixes and maps
of ecosystem service supply and demand can be merged. Supply
and demands have to be quantified in the same units in order to
be comparable. If the same units are not applicable, different units
need to be reclassified into the relative 0–5 scale. As a result we
get budgets of ecosystem service supply and demand. Fig. 4 shows
the corresponding matrix of ecosystem service budgets within
the different land cover classes. Each field in the budget matrix
was calculated based on the corresponding field in the supply
(Fig. 2) and the demand matrix (Fig. 3). The scale ranges from
As an example for a detailed quantitative assessment of
ecosystem service supply and demand, we calculated the provisioning ecosystem service “energy” for the rural-urban region
Leipzig-Halle in Eastern Germany. Rural-urban regions reflect
today’s complex interactions and dependencies between different
spatial categories within urban agglomerations. They are defined
as being composed of the urban area, the peri-urban area and
the rural hinterland (Ravetz et al., 2010). Being situated in the
former German Democratic Republic, the Leipzig-Halle region
experienced severe societal, economic, demographic and land use
related changes during the post-socialist transition period after
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
23
Fig. 3. Assessment matrix illustrating the demands for ecosystem services of humans living within the different land cover classes. The values/colors indicate the following
demands: 0/rosy = no relevant demand; 1/dark rosy = low relevant demand; 2/light red = relevant demand; 3/red = medium relevant demand; 4/dark red = high relevant
demand; and 5/brown red = very high relevant demand.
1990 (Nuissl and Rink, 2005). Land use changes include increasing
housing, industrial and traffic areas at the cost of agricultural land
and the increase of semi-natural areas, forests and water bodies
due to the restoration of several huge lignite open mining pits (see
land cover maps in Figs. 5 and 6; top left).
We quantified the supply and demand of energy as well as
the budgets of both for the years 1990 and 2007. In doing so, we
linked spatial and statistical data of energy supply and demand to
CORINE land cover maps of the respective years (German Federal
Environment Agency, 2004, 2006) (Figs. 5 and 6; top left). The
energy supply was calculated in GJ final energy per hectare land
cover type during the respective year. For that, the different energy
resources used in the region in 1990 and 2007 were identified and
assigned to the corresponding land cover types that were responsible for the energy provision. The identified energy resources,
corresponding land cover types, scales of quantification and data
sources used are summarized in Table 3.
The energy demand was calculated in the same unit as the
supply (GJ final energy per hectare per year) in order to guarantee
the direct comparability of supply and demand. For that purpose,
statistical data on energy demands of households, the service
sector, industry, traffic, mining and agriculture were applied and
values of energy demand per hectare of the respective land cover
types were calculated. The calculated energy demand and supply
values per hectare land cover type and (where appropriate) per
municipality or Federal State, were linked to the CORINE land cover
Table 3
Energy resources, corresponding land cover types, scales and data sources used for the quantification of energy supply in the case study region Leipzig-Halle.
Energy resources
Land cover type
Quantification scale
Data sources
Solar energy
Wind energy
Energy crops
Urban and industrial area
Agricultural area
Agricultural area
Municipality
Municipality
Federal State
Lignite
Mineral extraction sites
Mineral extraction site
Vattenfall Europe AG (2009)
Vattenfall Europe AG (2009)
Ministry for Agriculture and Environment Saxony-Anhalt (2002, 2007),
Saxon State Ministry of the Environment and Agriculture (2007),
Institute for Energy and Environment (2007)
Saxon State Department of the Environment and Geology (2004),
Saxon Upper Mining Authority (2002, 2007)
24
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
Fig. 4. Assessment matrix illustrating budgets of ecosystem services’ demand and supply (matrices in Fig. 2 and Fig. 3) within the different land cover classes. The values/colors
indicate budgets from −5/brown red = demand exceeds supply significantly = undersupply; via 0/rosy = demand = supply = neutral balance; to 5/dark green = supply exceeds
the demand significantly = oversupply. Empty fields indicate neither relevant supply of nor relevant demand for the particular ecosystem service.
maps of the years 1990 and 2006 in order to produce comparable
maps of energy supply and demand. CORINE data for the year 2007
are not available. Hence, there is one year difference between the
CORINE data and the statistical data from 2007, which seems to be
acceptable. The resulting values were then grouped into the above
described classes ranging from 0 (no relevant capacity/no relevant
demand) to 5 (very high relevant capacity/very high relevant
demand).
Subsequently, the maps of energy supply and demand were
intersected and spatially explicit energy budget maps were computed by subtracting energy demand values from energy supply
values of each land cover polygon. The resulting values were
grouped into classes ranging from −5 (demand exceeds the supply significantly) to +5 (supply exceeds the demand significantly).
Values near 0 indicate a balanced budget, i.e. the supply fits the
demand. For a more detailed description of energy supply and
demand quantifications, data sources used for energy demand calculations as well as further ecosystem service quantifications see
(Kroll et al., 2012).
3. Results
The resulting maps of the Leipzig-Halle case study area show the
spatial distribution of the provisioning ecosystem service energy
supply, related demands for energy and respective energy supply/demand budgets for the years 1990 and 2007 (Figs. 5 and 6).
The units in all six ecosystem service maps are final energy in GJ per
hectare per year. The legends were classified according to the 0–5
classes used in the ecosystem service matrices (Figs. 2–4). On the
figures’ top left are the CORINE land cover maps from the years 1990
and 2006 which provided the spatial reference and basic land cover
information. Within the EU project PLUREL2 , further ecosystem service supply and demand in the Leipzig-Halle region were calculated
and mapped; including food provision (supply and demand in GJ/ha
per year), global climate regulation (supply and demand of CO2
sequestration in t CO2 /ha per year) and water supply and demand
(m3 /ha per year); see (Kroll et al., 2012) and www.plurel.net. In
the following we will focus on examples from energy provisioning
ecosystem services.
3.1. Capacities to supply energy provisioning ecosystem services
The energy supply map for the year 1990 (Fig. 5; top right)
shows that exclusively the large lignite open mining pits were used
as energy sources in that period. They provided a vast amount
2
http://www.plurel.net/
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
25
Fig. 5. CORINE land cover map 1990 (top left); maps of energy supply (top right) and energy demand (bottom right); and budget map of energy supply and demand (bottom
right) for the rural-urban region of Leipzig-Halle, Germany in the year 1990 (energy data in GJ/ha/year).
of 20,000 GJ of final energy per hectare and year. This number
decreased by almost two thirds until 2007 due to a reduction in
mining areas and a reduced amount of extracted lignite (map in
Fig. 6; top right). Additionally, the use of the renewable energy
sources like wind, biomass, water and sun has appeared in the
region during the years until 2007. Wind energy was the most
important renewable energy source. All renewable energy sources
contributed less than 7% of the total final energy supply in the
region in 2007. In contrast to the locally discrete lignite mining
areas, renewable energy facilities occur area-wide. This becomes
very clear when comparing the maps from 1990 and 2007. In
1990, only the two extreme capacity classes are present, showing the maximum capacity (5) in the lignite pits and no relevant
capacity (0) in all other areas. In 2007, a broad range of capacities is distributed more or less equally over the whole area. Of
course, renewable energy facilities are locally discrete phenomena in reality as well. During the mapping process their locations
have been joined to the land cover classes’ polygons and thus,
their attributes were extrapolated to larger spatial extensions.
Moreover it has to be noticed that most changes in energy provision were not related to relevant changes in land cover types.
Most of the existing land cover types did not change between
1990 and 2007. Instead, the actual land use was modified by
adding renewable energy facilities on for example existing arable
land.
3.2. Human demands for energy provisioning ecosystem services
The energy demand data show a different picture: the highest
values can be found in industrial and commercial units, followed
by urban fabric and traffic areas as well as mineral extraction
sites. As the energy demand per hectare urban area depends on
the population density, it was the highest in the city centers
of Leipzig and Halle. The respective maps (Figs. 5 and 6; bottom left) show the area-wide occurrence of energy demand and
its concentration in the areas mentioned above. Energy demand
decreased by almost 20% from 1990 to 2007 due to declining population, decline of energy-intensive industrial activities as well
as more energy-efficient technologies. Nevertheless, the temporal
changes in the demand maps are not as obvious as in the supply
maps.
26
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
Fig. 6. CORINE land cover map 2006 (top left); maps of energy supply (top right) and energy demand (bottom right); and budget map of energy supply and demand (bottom
right) for the rural-urban region of Leipzig-Halle, Germany in the year 2007 (energy data in GJ/ha/year).
3.3. Budgets of energy provisioning ecosystem services’ supply
and demand
between 1990 and 2007 (compare the CORINE land cover maps in
Figs. 5 and 6; top left), reducing the energy supply by lignite.
The energy provisioning ecosystem services supply–demand
budget maps indicate dynamics in the production-consumption
respectively source-sink patterns. In the year 1990 (Fig. 5; bottom
right), when lignite was the only energy supplier in the region,
all areas in the region (except the mineral extraction sites) can
be characterized as sinks of energy provisioning ecosystem services. Especially the urban, industrial and commercial areas but
also the rural regions were dependent on flows of energy supplied
in only one land cover type. A different pattern emerges for the
year 2007 (Fig. 6; bottom right). Even though the urban, industrial
and commercial areas are still remarkable sinks of energy provisioning services, the amount and spatial extension of areas with
oversupply of energy have been increasing significantly due to the
area-wide use of renewable energy sources. In combination with
decreasing energy demands, the former dependence on only one
source of energy supply could be reduced on the one hand. On
the other hand, several open pit mining areas were closed down
4. Discussion
The maps illustrate the temporal dynamics of the spatial supply
and demand distributions in the case study area using the example
of energy provisioning ecosystem services for 1990 and 2007. For
some land cover types, the case study capacity values do not match
exactly with the initial hypotheses values provided for energy provision in the ecosystem service supply matrix (Fig. 2; for example
green urban areas). However, the majority of hypotheses values
were corroborated.
Supplementary data from statistics can improve the interpretation of the maps. For example, calculations of supply/demand ratios
for the energy provisioning ecosystem services provide information
on the total budget and the energy self-sufficiency of the whole
case study region. The supply/demand ratio was above 1 in 1990,
indicating that the energy supply (solely based on lignite) in the
region was higher than the demand (data references can be found
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
in Table 3). Then, several open pit mining areas were closed down
between 1990 and 2007 (compare the CORINE land cover maps in
Figs. 5 and 6; top left) and the lignite output has been reduced. As
a consequence, the whole case study region’s supply/demand ratio
declined to 0.5, indicating a clear dependence on energy imports
(data references in Table 3).
There is an ongoing debate within the ecosystem service
research community on whether natural resources are to be
denoted as ecosystem services or not. Lignite (fossil fuels in general), wind as well as solar energy have for example been denoted
as usually non-renewable abiotic resources which can neither be
attributed to specific ecosystems nor be called ecosystem services
(de Groot et al., 2002). We do not agree with this as wind and solar
energy are renewable inexhaustible natural services. In the case of
fossil fuels we conclude that it is actually depending on the temporal perspective (exchangeable by or in combination with higher
temperature and pressure), whether a resource is called renewable or not. The production function “raw materials” was defined
by de Groot et al. (2002; p. 396) as “the conversion of solar energy
into biomass for human use”, which is exactly what initially took
place during fossil fuel formation. Therefore we suggest denoting
all goods and services provided by every natural system to benefit
human well-being as ecosystem goods and services.
Looking at our ecosystem service mapping approach in general, several points worth discussing emerge. One major issue, not
really addressed yet, refers to questions related to spatial and temporal scales. Considering our approach to be a generic conceptual
model, it can be applied at any scale and would use data appropriate to the scale of analysis. Nevertheless, resolutions reflecting
peculiarity of the given habitats and temporal dynamics have to
be chosen. It seems like the CORINE data set and statistics based
on annual values are suitable starting points. For more detailed
analyses, further data with higher spatial (e.g. land survey data,
airphotos, topographic maps) and temporal (seasonal or monthly)
resolution could be used. With regard to the values in the matrices
(Figs. 2–4), it has to be taken into account that no real weighting
system between the different services was applied. Therefore, also
the calculated sums for the different ecosystem service groups in
the matrices provide only an overview on total service provision
with only limited accuracy when used for detailed interpretation.
One major shortcoming in the maps presented for our case study
is the inherent scale mismatch between supply and demand. On the
one hand, the supply of energy provisioning ecosystem services
could explicitly be related to respective supplying spatial units.
The demand for energy on the other hand was based on data on
spatially explicit final energy consumption but did not consider
where this energy was actually generated. Hence, real energy flows
between areas of supply and demands cannot be calculated based
on this information. Especially with today’s globalized trade systems including intercontinental cables, pipelines and trade routes,
origins and transport paths of a broad range of ecosystem services
are difficult to track. This is especially the case for provisioning
ecosystem goods and services (food, energy, material). Ecosystem
functions (ecological integrity) and regulating services are often
characterized by more or less physically connected areas of supply and demand. Most of these functions and services have to be
utilized or consumed at the same or a nearby locality from where
they are supplied, e.g. biomass production based on exergy capture,
large scale soil formation, (natural) pollination, nutrient regulation,
erosion control or flood regulation; (Nedkov and Burkhard, 2012).
Nevertheless, there are also regulating ecosystem services with
scale mismatches and delocalized causes and effects. One prominent example is global climate regulation, where a global demand
is supplied by local ecosystem functions. Another tricky point
is the proper assessment of cultural ecosystem services. Despite
the rather common (but nevertheless still not solved) difficulties
27
inherent to all intangible service assessments (Vejre et al., 2010;
Gee and Burkhard, 2010), we encountered additional problems
when defining spatial units of actual cultural ecosystem service
“consumption”. Are benefits like recreation, education or spiritual
enrichment consumed immediately at the place of their supply or
are they taken home to the place where people live for the most
time of the year? For the moment we decided to apply a consistent
way of thinking as for the other ecosystem services. Thus, people’s home places are defined as spatial units of ecosystem service
benefits, also with regard to cultural ecosystem services.
5. Conclusion
Mapping ecosystem service supply and demand and especially
the quantifying information behind these maps are important
contributions toward the applications of the ecosystem service
approach in science as well as in practice. Today’s ecosystem service
demand and consumption are far from being driven by actual supply; maps can help to visualize this mismatch. Certainly the demand
side has been neglected in most ecosystem service studies so far,
perhaps as data on demands are more difficult to collect than data
on production or costs (Ellis and Fisher, 1987). By adding ecosystem
service demand and budget matrices and corresponding maps to
our approach on ecosystem service supply maps presented before
(Burkhard et al., 2009), we hope to initiate further discussions and
to foster the development of appropriate tools.
Starting with matrices (as presented above) which are filled by
expert evaluations provides a rather easy tool to begin the ecosystem service assessments with. Expert hypotheses deliver a good
overview and “even imperfect measures of their [ecosystem services] value, if understood as such, are better than simply ignoring
ecosystem services altogether, as is generally done in decision making today” (Daily, 1997, p. 8). Levels of complexity and data accuracy
can then be increased successively. By using a “neutral” relative
scale (0–5), value-laden units (such as monetary terms) can be
avoided and a variety of data sources (e.g. monitoring, statistics,
expert judgment, literature review, on-site assessment) can be harmonized.
The selection of appropriate temporal and spatial scales as well
as appropriate system borders is crucial for ecosystem service
assessments. For mainly imported services (e.g. in urban regions),
a concept of ecosystem service footprints should be developed. For
local or regional decision making, trade-offs between the particular
services can be calculated. For example in our Leipzig-Halle case
study, the increase of energy crop cultivation negatively impacts
the regional food production. The decreased lignite extraction
again negatively influences the energy, but positively influences
the water supply (Kroll et al., 2012).
Besides the case study presented here, this assessment and
mapping approach has already been applied in further case studies (see Table 2). These applications showed that one main
obstacle in the evaluation of ecosystem services is the lack of
appropriate data for the quantification of the individual services’
supply and demand. Therefore, the development of corresponding
research projects, monitoring schemes, capacity building and further national ecosystem service assessments is suggested in order
to implement the concept of ecosystem services as a solution for
human–environmental problems and to provide a better data base
for the mapping of ecosystem services.
Acknowledgement
The work on the Leipzig-Halle case study was financially supported by the EU Integrated Project PLUREL (contract no. 036921).
28
B. Burkhard et al. / Ecological Indicators 21 (2012) 17–29
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